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Technical Report HCSU-011 PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE, HAWAI‘I Richard J. Camp 1 , Thane K. Pratt 2 , P. Marcos Gorresen 1 , John J. Jeffrey 3 , and Bethany L. Woodworth 2,4 1 Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo, Pacific Aquaculture and Coastal Resources Center, P.O. Box 44, Hawai‘i National Park, HI 96718, USA 2 U.S. Geological Survey, Pacific Island Ecosystems Research Center, P.O. Box 44, Hawai‘i National Park, HI 96718, USA 3 U.S. Fish and Wildlife Service, Hakalau Forest National Wildlife Refuge, 60 Nowelo St., Suite 100, Hilo, HI 96720, USA 4 Current address: Department of Environmental Studies, University of New England, 11 Hills Beach Road, Biddeford, ME 04005, USA Hawai‘i Cooperative Studies Unit University of Hawai‘i at Hilo Pacific Aquaculture and Coastal Resources Center (PACRC) 200 W. Kawili St. Hilo, HI 96720 (808) 933-0706 January 2009
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PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

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Page 1: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

Technical Report HCSU-011

PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE, HAWAI‘I

Richard J. Camp1, Thane K. Pratt2, P. Marcos Gorresen1, John J. Jeffrey3, and Bethany L. Woodworth2,4

1 Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo, Pacific Aquaculture and Coastal Resources Center, P.O. Box 44, Hawai‘i National Park, HI 96718, USA

2 U.S. Geological Survey, Pacific Island Ecosystems Research Center, P.O. Box 44, Hawai‘i National Park, HI 96718, USA

3 U.S. Fish and Wildlife Service, Hakalau Forest National Wildlife Refuge, 60 Nowelo St., Suite 100, Hilo, HI 96720, USA

4 Current address: Department of Environmental Studies, University of New England, 11 Hills Beach Road, Biddeford, ME 04005, USA

Hawai‘i Cooperative Studies UnitUniversity of Hawai‘i at Hilo

Pacific Aquaculture and Coastal Resources Center (PACRC)200 W. Kawili St.

Hilo, HI 96720(808) 933-0706

January 2009

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The view and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Government. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Government.

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Technical Report HCSU-011

PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE, HAWAI‘I

Richard J. Camp1, Thane K. Pratt2, P. Marcos Gorresen1, John J. Jeffrey3, and Bethany L.

Woodworth2,4

1 Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo, Pacific Aquaculture and Coastal Resources Center, P.O. Box 44, Hawai‘i National Park, HI 96718, USA 2 U.S. Geological Survey, Pacific Island Ecosystems Research Center, P.O. Box 44,

Hawai‘i National Park, HI 96718, USA 3 U.S. Fish and Wildlife Service, Hakalau Forest National Wildlife Refuge,

60 Nowelo St., Suite 100, Hilo, HI 96720, USA 4 Current address: Department of Environmental Studies, University of New England,

11 Hills Beach Road, Biddeford, ME 04005, USA

CITATION Camp, R.J., T.K. Pratt, P.M. Gorresen, J.J. Jeffrey, and B.L. Woodworth. (2009).

Passerine bird trends at Hakalau Forest National Wildlife Refuge, Hawai‘i. Hawai‘i Cooperative Studies Unit Technical Report HCSU-011. University of Hawai‘i at Hilo. 38

pp., incl. 6 figures, 3 tables & 5 appendices.

Keywords: bird counts; densities; Hakalau Forest National Wildlife Refuge; Hawai‘i; point-transect sampling; population trends

Hawai‘i Cooperative Studies Unit

University of Hawai‘i at Hilo Pacific Aquaculture and Coastal Resources Center (PACRC)

200 W. Kawili St. Hilo, HI 96720 (808)933-0706

January 2009

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This product was prepared under Cooperative Agreement CA03WRAG0036 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey

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Table of Contents ABSTRACT........................................................................................................................ 1 INTRODUCTION .............................................................................................................. 3 METHODS ......................................................................................................................... 5

Study Area ...................................................................................................................... 5 Bird Species .................................................................................................................... 5 Bird Sampling ................................................................................................................. 6 Density Estimation.......................................................................................................... 6 Trend Detection .............................................................................................................. 8

RESULTS ........................................................................................................................... 9 DISCUSSION................................................................................................................... 11 ACKNOWLEDGMENTS ................................................................................................ 14 LITERATURE CITED ..................................................................................................... 15

List of Tables Table 1. Trends in forest bird density. ............................................................................. 19 Table 2. Forest bird abundance estimates in 2007........................................................... 19 Table 3. Bird detection probability over time.................................................................. 23

List of Figures Figure 1. Hakalau Forest NWR relative to general landcover types ................................ 24 Figure 2. Density estimates of native bird species at Hakalau Forest NWR .................... 25 Figure 3. Density estimates for alien bird species at Hakalau Forest NWR..................... 26 Figure 4. Density estimates for species in reforested pasture at Hakalau Forest NWR. .. 27 Figure 5. Density estimates for Hawai‘i ‘Amakihi in the middle study area ................... 28 Figure 6. Native passerine population trends in five regions of Hawai‘i Island............... 29

List of Appendices Appendix 1. Model Selection and AIC............................................................................ 29 Appendix 2. Species Data and Models. ........................................................................... 32 Appendix 3. Population density estimates in the middle study area................................ 35 Appendix 4. Population density estimates in the lower study area.................................. 37 Appendix 5. Population density estimates in the upper study area.................................. 38

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ABSTRACT

Hakalau Forest National Wildlife Refuge, on the Island of Hawai‘i, was established in 1985 to protect native forest birds, particularly endangered species. Management actions on the 15,400 ha refuge include removing feral ungulates from the forest and pastures, controlling invasive alien plants, reforesting pastures, and supplementing endangered plant populations. To assess effects of this habitat improvement for birds, we calculated annual density estimates from point transect surveys and examined population trends for eight native and four alien passerine bird species over the 21 years since the refuge was established (1987-2007). We examined trends using a Bayesian approach to log-linear regression. We tested for changes in bird density in three study areas: (1) a middle elevation forest that had been heavily grazed, (2) an upper elevation pasture that was reforested during the study, and (3) a lower area of relatively intact forest that was formerly lightly grazed. In the middle study area, we found that densities of Hawai‘i ‘Elepaio (Chasiempis s. sandwichensis), and the endangered ‘Akiapōlā‘au (Hemignathus munroi) and Hawai‘i Creeper (Oreomystis mana) increased, and that all other native birds showed stable trends and exhibited no evidence of declining trends as has been seen elsewhere in much of Hawai‘i. Trends for all alien birds were also stable, except that House Finch (Carpodacus mexicanus) density has declined. In the lower study area, Hawai‘i Creeper and Hawai‘i ‘Ākepa (Loxops c. coccineus) showed increasing trajectories, and densities have declined for the other native species. Within the reforested upper study area, densities increased for three common native species—Hawai‘i ‘Amakihi (Hemignathus virens), ‘I‘iwi (Vestiaria coccinea), and ‘Apapane (Himatione sanguinea)—and two alien species—Japanese White-eye (Zosterops japonicus) and House Finch. Bird trends at the Hakalau refuge provide some of the first results of habitat improvement for forest birds in Hawai‘i. Restoring tree cover in open pasture and assisting recovery of high-quality habitat benefits both endangered and abundant native birds.

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INTRODUCTION It is widely recognized that native Hawaiian birds are greatly imperiled (BirdLife

International 2000, Scott et al. 2001). Naturalists from the 1890s through 1950s witnessed declining populations, contracting species’ ranges, and a great many extinctions (Banko and Banko, in press). Even in the modern period of conservation activity in the Hawaiian Islands, population trends for most species have been downwards, with perhaps as many as 10 extinctions from 1977-2007 (Scott and Kepler 1985; Gorresen et al., in press). Despite some successes in Hawaiian seabird and waterbird conservation (BirdLife International 2000), reversing declines in forest birds has been particularly challenging owing to continued deterioration of habitat and harmful effects of invasive alien species (Price et al., in press).

Comprehensive surveys from 1976 to 1981 by Scott et al. (1986)—the Hawai‘i Forest Bird Survey or HFBS—provided the first quantitative estimates of Hawaiian forest bird populations. These authors established that the majority of native land birds survived mainly at high elevations above the limits of avian diseases, the mosquito vectors that transmit them, and other factors resulting in habitat deterioration and depletion of food resources. Recovery planning since has depended on habitat restoration of montane forests as its principle strategy (U.S. Fish and Wildlife Service 2006). The approaches to habitat restoration mainly include removing domestic livestock and feral ungulates, controlling invasive alien plants, and reforestation. In nearly all cases, however, habitat improvement projects are relatively new—mainly since the 1980s—and their impacts on forest bird populations has not been previously studied.

Scott et al. (1986) also identified geographic gaps in forest bird protection. These authors overlaid bird diversity maps onto land ownership and management maps, a prototype of gap analysis. Results revealed that the largest populations of forest birds and prime habitat on Hawai‘i Island fell outside the best-protected areas (U.S. Fish and Wildlife Service 1982). Furthermore, this process identified those areas where protection and management would most benefit native Hawaiian forest birds. Ranking high among the top priority sites were the high-elevation rainforests on the dormant volcano Mauna Kea. Here, the first national wildlife refuge to protect and restore Hawaiian forest birds was established in 1985—the Hakalau Forest National Wildlife Refuge (hereafter, Hakalau Forest NWR, Hakalau, or just refuge). (To avoid confusion, it is necessary to mention that there are two units to this refuge: the main Hakalau Forest Unit which is the subject of our report, and the Kona Forest Unit on the western side of the island.)

Hakalau is an important test case for habitat improvement as a tool for restoring populations of Hawaiian forest birds because of its relatively early establishment, history of active habitat management, large area, and the long-term monitoring of its bird populations. As is typical over much of the best forest bird habitat on Hawai‘i Island, the upper elevation koa (Acacia koa) forest in the area that is now the refuge was converted to cattle pasture in the 1800s, leading to replacement of forest cover by a non-native grassland (Scott et al. 1986). An additional environmental stressor to forest health has been the feral pig (Sus scrofa). Through rooting and herbivory, pigs browse native plants, damage soils, inhibit native plant regeneration, alter nutrient cycling, and disperse alien plants (Hess et al. 2006), and pigs create mosquito breeding habitat (Atkinson et al. 1995, Aruch et al. 2007). The eradication of feral cattle (Bos taurus) and pigs has been a primary management goal at Hakalau (Feral Ungulate Management Plan: U.S. Fish and

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Wildlife Service 1996). To date, the refuge has installed 72 km of fencing surrounding eight management units that total more than 5,700 ha (37% of the refuge). About 4,800 ha (85%) of the management units are now ungulate free or nearly so (Maxfield 1998, Hess et al. 2006).

Weed control has also been implemented by Hakalau Forest NWR to improve forest bird habitat. Invasive gorse (Ulex europaeus), blackberry (Rubus argutus), banana poka (Passiflora mollissima), and holly (Ilex aquifolium) are being treated on about 2,200 ha, essentially the entire area where these weeds occur in the refuge (Hakalau Forest NWR, unpub. data).

Reforestation has occurred on the approximately 2,000 ha of former pasture in the upper elevations of the Hakalau Forest NWR (Fig. 1). More than 400,000 native tree seedlings, mainly koa, have been out-planted since 1987 (Hakalau Forest NWR, unpub. data). Native birds now utilize these plantations. For example, the ‘Akiapōlā‘au, an endangered species, has been observed foraging in planted koa 1.5 km away from old growth forest (J. Jeffrey, USFWS, pers. obs). In addition to providing habitat directly, it is hoped that forest restoration will help mitigate against the threat of global climate change by extending bird habitat to higher elevations and outpace the upslope expansion of disease-vectoring mosquitoes (Benning et al. 2002).

Detecting and interpreting trends in bird populations and their response to management activities are important components of assessing management and conservation actions at Hakalau Forest NWR. Annual bird surveys have been conducted at Hakalau since 1987 in formerly grazed forest and reforested grassland between 1,300 and 2,100 m, and sample about 35% (5,500 ha) of the refuge. An additional 1,100 ha has been surveyed annually since 1999 to examine bird trends in relatively intact forest at lower elevations (1,400-1,700 m). Such long-term datasets of population densities are useful for describing baseline variability in populations, detecting biologically relevant changes, and informing of population responses to management actions (Camp et al., in press). Thus, the frequent and long-term monitoring of forest birds at Hakalau offers one of the best opportunities to examine the outcome of habitat improvement for forest birds in Hawai‘i.

The purpose of this study is to appraise changes in forest bird populations in light of habitat restoration. Native bird populations are decreasing at many locations on Hawai‘i Island (Gorresen et al., in press). Are native bird populations stable or increasing at Hakalau? Are all forest birds showing similar trends, or does species ecology and degree of threat correlate with differing trend patterns? Although identification of a causal relationship between restoration activities and changes in the bird populations is not possible from these time series data, it is reasonable to expect that the habitat changes underway at the refuge influence bird trends and could halt or reverse population declines. We examine this expectation by comparing trends in native birds within Hakalau to trends in populations outside the refuge that are under different forest and ungulate management. The encouraging results reported here from Hakalau Forest NWR are of practical use to land managers and agencies protecting and restoring Hawaiian forest birds, and of theoretical use to scientists investigating the relationship between forest restoration and bird conservation.

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METHODS

STUDY AREA The 15,390 ha Hakalau Forest NWR (19o 51’N, 155o 18’W) on the windward

slope of Mauna Kea volcano is the largest protected and actively managed area of mid- to high-elevation rain forest on the Island of Hawai‘i and in the state of Hawai‘i (Fig. 1). Mean daily air temperature averages 15oC with an annual variation of <5oC, and annual rainfall averages 2,500 mm with a maximum of about 6,100 mm (Juvik and Juvik 1998). The montane forest has a canopy dominated by old-growth ‘ōhi‘a-lehua (Metrosideros polymorpha) and koa (Scott et al. 1986). ‘Ōlapa (Cheirodendron trigynum), kōlea (Myrsine lessertiana), pilo (Coprosma montana, C. ochracea, and C. rhynchocarpa), tree ferns (Cibotium spp.), pūkiawe (Styphelia tameiameiae), ‘ōhelo (Vaccinium calycinum), and ‘ākala (Rubus hawaiiensis) are the most common subcanopy trees and shrubs. Vegetation at middle elevations (600–1,900 m) is dominated by native ‘ōhi‘a and koa/‘ōhi‘a forest, whereas at the highest elevations (>1,900 m) it is comprised of open grassland and relict mature koa trees and recent forest plantations (Fig. 1). Nonnative plant species may be found in native forest at all elevations, the most injurious species being various pasture grasses, gorse, blackberry, banana poka, and holly.

For purposes of analysis, the refuge was divided into three study areas. The middle area includes once intensively grazed forest at an elevational range of 1,400-1,920 m (area = 3,373 ha); this area has been surveyed the longest, since 1987 with on average 277 stations. The lower area is forest relatively unmodified by grazing, and it has been surveyed since 1999 with 197 stations (area = 1,998 ha). Its ecological significance to forest bird management on the refuge is that, because of its lower elevation (1,400-1,700 m), declines in native birds due to avian disease might be expected to appear there first (van Riper and Scott 2001). Lastly, the upper area at 1,650-2,000 m elevation was open pasture at the beginning of the study and was reforested so that by the end of the study period it included planted stands of koa trees up to 20 years old; it was surveyed intermittently since 1987 with 35 stations (area = 1,314 ha). Survey data from 1992 to 1995 and 1997 in the upper study area were not used in our analyses because fewer than 30 stations were sampled.

BIRD SPECIES We produced abundance and trend estimates for eight native and four introduced

species. Only a small portion—11 species—of the refuge’s original avifauna survives. The missing component includes as many as 13 historically known species that could once have occurred on the refuge, but these are now either extinct or have withdrawn from the area that is now the refuge, together with an unknown number of species that disappeared before Western contact in the late 18th century (Banko and Banko, in press). Native bird densities decline at lower elevations, and several species are essentially absent from the lowest elevations of the refuge. Our survey methods (see below) were effective at sampling the eight extant forest passerines present on the refuge but were not suitable for estimating densities of the ‘Io (Hawaiian Hawk; Buteo solitarius), Pueo (Short-eared Owl; Asio flammeus), and Nēnē (Hawaiian Goose; Branta sandvicensis), and data for those species are not presented here.

The eight native forest bird species sampled are all passerines. The Hawai‘i ‘Elepaio is a monarch flycatcher (Monarchidae), and the ‘Ōma‘o (Myadestes obscurus) is

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a thrush (Turdidae). Six Hawaiian honeycreepers (Fringillidae: Drepanidinae) include the ‘Akiapōlā‘au, Hawai‘i ‘Amakihi, Hawai‘i Creeper, Hawai‘i ‘Ākepa, ‘I‘iwi, and ‘Apapane. The ‘Akiapōlā‘au, Hawai‘i Creeper, and Hawai‘i ‘Ākepa are federally and state listed endangered species, and Hakalau Forest NWR encompasses a significant portion of their ranges. In addition, 16 species of introduced birds now occupy the refuge, but only four of these have invaded the forest and exist in densities that can be readily tracked: Red-billed Leiothrix (Timaliidae; Leiothrix lutea;), Japanese White-eye (Zosteropidae), Northern Cardinal (Cardinalidae; Cardinalis cardinalis), and House Finch (Fringillidae).

BIRD SAMPLING The HFBS sampled the Hakalau Forest NWR area in 1977 along three transects

spaced about 3 km apart with 95 stations at 134 m intervals (Scott et al. 1986). Soon after establishment of the refuge, a new series of 11 transects was laid out and later expanded to a total of 15 transects, with a range of 196 to 343 stations. Annual bird sampling commenced in 1987. Distances between stations varied from 134 m to 250 m. By comparison, most other studies in Hawai‘i have used a 150-m interval between stations to reduce the likelihood of double-counting birds (Reynolds et al. 1980, Scott et al. 1986). All surveys have followed the same point-transect sampling procedures implemented by Scott et al. (1986).

Observers received pre-survey training to calibrate for distance estimation and learn bird vocalizations, thereby minimizing variability among observers and standardizing for local conditions (Kepler and Scott 1981, Scott et al. 1986, Verner and Milne 1989). Observers recorded the detection type (heard, seen, or both) and horizontal distance from the station center point to individual birds detected during an 8-min count. They also recorded cloud cover, rain, wind, gust, and time of day at each station. Sampling was typically conducted between dawn and 1100 hr and halted when rain, wind, or gust exceeded prescribed levels.

The detectability of forest birds varies throughout the year, due to changes in vocal activity associated with breeding (Best 1981), and birds may move in or out of the study area in response to phenology of food resources (Simon et al. 2002). To minimize biases associated with differences in sampling periods, we restricted density estimates to the breeding season only. The original 1977 HFBS was conducted in July, a month when breeding within the bird community has generally finished and many nectarivorous birds have dispersed in search of flowers (Scott et al. 1986; Ralph and Fancy 1994, 1995). Since the HFBS, annual surveys from 1987 to 2007 were conduced mainly during March and April to correspond with the breeding season for the most species. Because of this disparity in the months sampled, and the great difference in number and location of stations sampled, we excluded the HFBS data from our analyses.

DENSITY ESTIMATION As a form of distance sampling, point-transect methods are used to correct

abundance estimates for individuals that go undetected. This is accomplished by modeling a species-specific detection function and calculating a probability of detection, which is subsequently used to estimate bird density (Buckland et al. 2001). Robust estimates are reliant upon the critical assumptions that all birds are detected with certainty at the station center point, birds are detected prior to any responsive movement,

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and distances are measured without error. Buckland et al. (2001, 2004) describe distance sampling procedures and analyses in detail.

We present density estimates only for species with sufficient detections (>500) to adequately characterize detectability. In addition, we calculated the 2007 total abundances for these species by multiplying the strata-specific density by the area of each study area stratum. Species-specific density estimates (birds/ha) were calculated from point-transect data using program DISTANCE, version 5.0, release 2 (Thomas et al. 2005). Data were truncated at a distance where detection probability was <10%. This procedure facilitates modeling by deleting outliers and reducing the number of adjustment parameters needed to modify the detection function. Candidate models were limited to half normal and hazard-rate detection functions with expansion series of order two (Buckland et al. 2001:361, 365). The uniform detection function was not considered because covariates cannot be modeled. To improve model precision, we incorporated sampling covariates in the multiple covariate distance sampling (MCDS) engine of DISTANCE (Marques and Buckland 2004, Thomas et al. 2005). Covariates included cloud cover, rain, wind, gust, observer, time of detection, and month of survey. Each detectability model in the candidate set was fitted to each species, and the model selected was that with the lowest Akiake’s Information Criterion (AIC) and where the proportion of variance in the model due to variability in the detection function was less than 70% (Buckland et al. 2001; Burnham and Anderson 2002; K. Burnham, pers. comm.; Appendix 1).

A hazard-rate key function with a covariate representing observer provided the best approximating model for ‘Ōma‘o and Hawai‘i ‘Ākepa distance measures (Appendix 2). This same key detection function with a cosine adjustment term was fit to the Red-billed Leiothrix distance measures, and with a simple polynomial adjustment term for Japanese White-eye. A hazard-rate key function, without adjustment terms or covariates, was fit to the ‘Akiapōlā‘au and ‘Apapane distance measures, and with a cosine adjustment term for Hawai‘i Creeper. Hawai‘i ‘Elepaio and Hawai‘i ‘Amakihi distance measures were fit with the half-normal key function with a covariate representing observer. The half-normal key function without covariates was fit to the ‘I‘iwi distance measures, and with a cloud covariate for Northern Cardinal.

A concern when monitoring birds over a long period is that successional changes in the vegetation may affect bird detectability and thereby influence measurement of density and trend. As the forest becomes thicker, birds may become more difficult to see and hear, and counts may go down even when populations are not decreasing. The upper forests of Hakalau were once little more than wooded parkland, a result of more than a century of cattle grazing. Over the past two decades of habitat management at the refuge, bird counters have observed that the forest structure has become increasingly dense and complex. We therefore assumed that detection probabilities, ˆ ip , may vary through time and be survey specific. We developed seven time-specific detectability models by pooling bird detections over different numbers of years (year-specific [1-year groups], 2-year groups, 5-year groups, etc.) and incorporated the number of years pooled as a covariate in MCDS modeling. We used AIC to rank the models and choose whether to pool across years or not. Annual density estimates were calculated by post-stratifying detection data by each group of ˆ ip s for the model with lowest AIC. We tested for changes in bird detectability by estimating the posterior probability of a trend within a

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Bayesian framework (see Trend Detection below). We used a 10% change in detection probabilities in 25 years as the threshold for defining the ecological relevance of a trend.

However, the pattern of annual variability in the detection probabilities contributed to our decision to estimate densities from survey-specific models instead of using a global model. Densities are typically calculated from global models that assume constant detection probabilities ( ˆ ip ). These models do not account for survey-specific detection probabilities and may obscure trends that in turn affect density estimation. Variable ˆ ip s can be modeled as covariates using multiple covariate distance sampling

procedures, but the global modeling approach uses an average ( ˆ ip ) instead of survey-specific ˆ ip to estimate densities. An alternative approach is to fit a global model to the whole data set and then apply this model to the individual survey data, a post-filtering approach. The post-filtering approach fixes the detection function shape but the scale of the detection function is allowed to change for the individual survey data. We generated ˆ ip s and annual densities using three approaches: modeling each year independently

(survey-specific approach), filtering the detection data by year group (post-filtering approach), and a global modeling post-stratification approach. We conclude that estimates were in agreement when the 95% CI bracketed mean densities estimates from alternative approaches.

TREND DETECTION We defined population trend as the long-term, overall pattern in abundance over

time. A long-term trend may be composed of short-term fluctuations or trajectories that vary over time and that may persist for only a few years. Relying on short-term trajectories to describe population patterns can be misleading when extrapolated; however, they can also be illuminating, especially as they may indicate the start of a shift in the trend. Long-term trends in bird density were assessed for a 21-year period (1987-2007) for the middle and upper (reforested pasture) study areas. Short-term trajectories for the middle and lower study areas were calculated for a 9-year period (1999-2007) when these forested tracts were concurrently surveyed; this is also the most recent period and may give indications to changes in the long-term trends.

We assessed change in populations by estimating the posterior probability of a trend or trajectory within a Bayesian framework. The Bayesian approach provides an intuitive assessment of the trend, and the method is particularly useful for distinguishing between ecologically negligible and meaningful trends (Wade 2000, Camp et al. 2008). In contrast, conventional trend analysis is unable to provide conclusive evidence that a trend is near or at zero, nor distinguish such from actual trends masked by the effects of high variance in statistically non-significant outcomes.

We used a log-link regression model to calculate the distribution of the posterior probabilities of the slope ( β̂ ) using WinBUGS (Lunn et al. 2000) in program R (R version 2.7.0; 2008-04-22; The R Foundation for Statistical Computing). The parameter α describes the density at time t = 0 (i.e., intercept), β is the rate of change (i.e., slope) with each unit increase in time t, and τ equals 1/variance (i.e., precision). The parameters α and β were given uninformative normal priors, and an uninformative gamma prior was given for τ. An uninformative prior distribution was chosen to restrict the posterior distribution to the likelihood, which was dominated by the observed data. The trends

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were centered; 1997 for the 1987 to 2007 period, and 2002 for the 1999 to 2007 period. The model parameters were estimated from 50,000 iterations for each of three chains (i.e., model runs) after discarding the first 2,000 iterations (a “burn-in” period). The three chains were pooled (150,000 total samples) to calculate the posterior distribution.

We used a 25% change of a population in 25 years as the threshold for defining the ecological relevance of a trend. The Breeding Bird Survey uses a 50% change over 25 years to assess trends (Peterjohn et al. 1995); however, we felt this was not sensitive enough to detect trends in endangered species so we halved the magnitude change to 25%. Trends were defined as an ecologically meaningful decrease when the slope exceeded the lower threshold ( β̂ < -0.0119), an ecologically meaningful increase when the slope surpassed the upper threshold ( β̂ > 0.0093), and an ecologically negligible trend when the slope fell within the threshold levels (-0.0119 < β̂ < 0.0093) (Camp et al. 2008).

We interpret the likelihood of a trend with four categories of evidence derived from the posterior odds (also called Bayes factors): very weak, weak, strong, or very strong evidence (Wade 2000). We defined the categories based on the posterior probability (P) limits of: very weak if P < 0.1; weak if 0.1 ≤ P < 0.7; strong if 0.7 ≤ P < 0.9; and very strong if P ≥ 0.9. In cases where the posterior odds provide weak evidence among all three trend categories (i.e., decreasing, negligible, and increasing trends), we interpret the trend to be inconclusive (referred to as “no consensus” by Crome et al. 1996). We conclude that a population was “stable” given strong or very strong evidence of a negligible trend. Trends were interpreted as stable to increasing or stable to decreasing in cases where the posterior odds provided weak evidence for both the negligible category and either the increasing or decreasing category, and very weak evidence for the remaining category.

RESULTS Of the total of 11 native birds on the refuge, we had sufficient information to

calculate densities for eight species— Hawai‘i ‘Elepaio, ‘Ōma‘o, Hawai‘i ‘Amakihi, ‘Akiapōlā‘au, Hawai‘i Creeper, Hawai‘i ‘Ākepa, ‘I‘iwi, and ‘Apapane—and four alien birds—Red-billed Leiothrix, Japanese White-eye, Northern Cardinal, and House Finch (Appendices 3-5). One of the most significant and positive findings of this study was that density of Hawai‘i ‘Elepaio, ‘Akiapōlā‘au, and Hawai‘i Creeper have conclusively increased within the middle study area of Hakalau Forest NWR over the 21-year period (Tables 1 and 2, Fig. 2). That is, those species’ densities showed a trend that would result in its population increasing by 38%, 165%, and 49%, respectively, over a 25 year period. Another positive finding was the evidence of stable to increasing long-term trends for Hawai‘i ‘Ākepa and ‘Ōma‘o during the same period. Moreover, no native species was found to have declined in density in the middle study area over the 21-year period—we detected very strong evidence of stable trends for Hawai‘i ‘Amakihi, ‘I‘iwi, and ‘Apapane (Tables 1 and 2, Fig. 2).

In addition to long-term trends, we examined shorter-term (1999-2007) trajectories in the middle and lower study areas. In the lower study area, only Hawai‘i Creeper and Hawai‘i ‘Ākepa showed evidence of increasing trajectories. In contrast

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‘I‘iwi and ‘Apapane densities were stable to decreasing. ‘Ōma‘o, Hawai‘i ‘Amakihi, and ‘Akiapōlā‘au showed declining trajectories, and the Hawai‘i ‘Elepaio trajectory was not estimated well enough to make strong conclusions. Short-term trajectories in the middle study area were declining for all of the native birds, except ‘Ōma‘o, which had a stable trajectory, and ‘Akiapōlā‘au and Hawai‘i Creeper, which showed inconclusive trajectories (Table 1, Fig. 2).

For the introduced birds in the middle study area, Red-billed Leiothrix and Japanese White-eye trends during the 21-year period were stable, and Northern Cardinal trends were stable to declining (Tables 1 and 2, Fig. 3). House Finch densities decreased during both the 21-year and recent 9-year periods, and a declining trajectory was also detected for the Red-billed Leiothrix and Northern Cardinal. The Japanese White-eye was stable to increasing since 1999 in the middle study area. In the lower study area, Japanese White-eyes showed an increasing trajectory, while the trajectory for Red-billed Leiothrix was decreasing; data were insufficient for the other two alien species. Thus, Japanese White-eye was the only alien species to show increasing density in the forested areas of the refuge, and this was observed only in the short-term trajectories.

In the upper study area, count data indicate that reforestation of pastures has benefited certain species of native and alien birds. Hawai‘i ‘Amakihi, ‘I‘iwi, ‘Apapane, Japanese White-eye, and House Finch showed strong or very strong evidence of increasing long-term trends, and their densities have more than doubled over the last 21 years (Tables 1 and 2, Fig. 4). Notably, Japanese White-eye showed a marked increase in numbers, and their densities were about twice that in the adjacent forest habitats. Although all three of the endangered species—‘Akiapōlā‘au, Hawai‘i Creeper, and Hawai‘i ‘Ākepa—have been observed using restored pasture, trends for the three endangered species could not be determined because of insufficient numbers of detections.

We tested the supposition that bird detectability is decreasing as the forest recovers. Detection probabilities decreased at a marginal rate for all native birds and Japanese White-eye, except ‘Akiapōlā‘au which increased slightly (Table 3). Slight increasing trends were also found for House Finch, and there is strong evidence of increasing detection probabilities for Red-billed Leiothrix and Northern Cardinal. Only Hawai‘i ‘Elepaio showed strong evidence of decreasing trends in detection probabilities. All other birds showed negligible or inconclusive trends. Thus, the detection probabilities for all species except Hawai‘i ‘Elepaio have not decreased over time despite increasing vegetation cover, indicating habitat recovery may be hindering bird detectability for only one species.

We used Hawai‘i ‘Amakihi data to assess whether density estimates were comparable among estimates generated from modeling ˆ ip s by the three approaches: (1) survey-specific, (2) post-filtering, and (3) global model (Fig. 5). Comparing estimates generated from survey-specific and global models yielded only a 27% agreement. There was 59% agreement between the post-filtering and global model density estimates. There was better agreement (64%) between density estimates generated by the survey-specific and post-filtering approaches. Since both survey-specific and post-filtering approaches allow ˆ ip s to vary annually and yielded similar results, and because most species showed negligible evidence of decreasing in ˆ ip s, we conclude that either approach will perform reasonably well and produce reliable density estimates.

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DISCUSSION An important finding of this study is that no species of native bird showed a

decreasing trend over the full 21-year monitoring period in the middle study area, where forest management and bird monitoring have been conducted the longest. Furthermore, we detected increasing densities in this area for the Hawai‘i ‘Elepaio and endangered ‘Akiapōlā‘au and Hawai‘i Creeper. ‘Akiapōlā‘au make use of young stands of koa trees and have directly benefited from plantings and natural recruitment of koa (Pejchar et al. 2005). A likely cause for improvement in the ‘Akiapōlā‘au population is the documented increase in wood-boring beetles, an important prey source (Goldsmith et al. 2007). All native birds may be responding favorably within the middle study area to the regeneration of native ferns and woody plants following ungulate removal (Hess et al. in review). While our study does not demonstrate cause-effect responses of population trends to management actions, it reveals a striking contrast between the stable to increasing trends at Hakalau Forest NWR and the declining trends in forest bird populations at other high-elevation sites on Hawai‘i Island, specifically at central windward region, Ka‘ū, central Kona, and Hualālai (Fig. 6). In these localities where intensive forest management is absent, widespread declines have been reported for Hawai‘i ‘Elepaio and ‘I‘iwi and local declines observed for ‘Akiapōlā‘au, Hawai‘i Creeper, and Hawai‘i ‘Ākepa (Reynolds et al. 2003; Gorresen et al. 2005, 2007; Tweed et al. 2007; Gorresen et al., in press).

Another important finding of this study is that reforestation of former pastures has begun to benefit native birds. The Hawai‘i ‘Amakihi, ‘I‘iwi, and ‘Apapane showed increasing trends in density in the upper area, and Hawai‘i ‘Amakihi has been observed foraging and nesting in this restored habitat (J. Jeffrey, pers. obs.). The endangered ‘Akiapōlā‘au has also been observed foraging in reforested pastures, and it is likely that other native birds are also beginning to respond to reforestation, but the small sample sizes in this area make it difficult to detect population changes. Continued monitoring will be needed to determine if the increasing trends continues as expected, and whether additional species begin to show population responses.

Nevertheless, we expected that populations of common native birds—Hawai‘i ‘Elepaio, ‘Ōma‘o, Hawai‘i ‘Amakihi, ‘I‘iwi, and ‘Apapane—would increase in response to management actions in the forested areas at Hakalau Forest NWR, but this generally was not the case. Evidence of increasing density was observed for Hawai‘i ‘Amakihi, ‘I‘iwi, and ‘Apapane in reforested pasture, as described above, but except for increasing density in Hawai‘i ‘Elepaio, densities of common native birds showed stable trends in the middle elevation study area. One possible explanation for why we did not observe increases in the common species is that the geographic extent of management actions does not encompass sufficient portions of their range to effect a change. Forest regeneration and plantings in the managed areas constitute only a fraction of the birds’ range on Hawai‘i Island. For example, both ‘I‘iwi and ‘Apapane occur throughout and outside the refuge (Scott et al. 1986), and, unlike the endangered species, these birds exhibit long-distance movements to track the seasonal and patchy distribution of ‘ōhi‘a flowering (Fancy and Ralph 1997, 1998). Thus, they are exposed to disease at low elevations. It is possible that limiting factors operating at larger geographic scales, such as an upslope expansion of avian diseases (Benning et al. 2002, Freed et al. 2005), might

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be counteracting the local benefits of habitat improvement for these and other widespread species.

Another possible explanation for not detecting increasing trends in most native species is that their rate of response may be fairly slow. The rate of increase we chose to test for was a 25% change in the population density in 25 years—a threshold used to alert managers to potentially serious declines. Perhaps such a high rate of increase is too much to expect. It may be that populations of native birds are increasing but at a slower rate. For example, the annual rates of change for ‘Ōma‘o, Hawai‘i ‘Amakihi, Hawai‘i ‘Ākepa, ‘I‘iwi, and ‘Apapane were very small. Somewhat higher rates of change, 1-2% per year, were observed for Hawai‘i ‘Elepaio and Hawai‘i Creeper, and these increases will add up over time. It would take about 35 years for a population to double at a 2% annual rate of increase.

Lastly, bird numbers may not show a greater rate of increase until habitat recovery at Hakalau advances beyond the early stages. Forest recovery is only 20 years along in a process that will take hundreds of years, and there may be a lag time before most bird populations markedly increase. While the success with koa reforestation is important, other tree and shrub species that comprise ecologically important components of the forest are much slower to recruit on their own and are more difficult to cultivate and out-plant. ‘Ōhi‘a-lehua—the dominant forest tree crucially important to birds for its nectar-bearing flowers, arthropod prey-base, and nest sites—grows much slower than koa (Lamoureux et al. 1981). It will be many decades before a tall forest of diverse composition once again covers the formerly grazed and recently reforested portions of the refuge.

A final concern is the apparent recent decline in bird density forecast by the short-term (9-year) trajectories of certain native species in the recovering middle and lower study areas. Without these negative trajectories, the overall trends for the 21 year period would have shown stronger, positive slopes. If the near-term trajectories continue downwards, it will not be long before some species begin to show negative overall trends.

One explanation for the change in trajectories, generally down in both the middle and lower strata since the mid- to late-1990s, is that birds may be responding to decadal fluctuations or longer term changes in climate. Hawai‘i is currently experiencing a drying trend in the Pacific Decadal Oscillation (Chu and Chen 2005). There are few quantitative studies that might explain how rainfall patterns affect Hawaiian forest bird ecology such as food availability, nest success, and thermal stress, and research is needed to provide insight.

Other possible explanations for apparent recent declines might include an increase in one or more established threats, such as upslope expansion of mosquitoes and avian disease, an increase in predatory rats in response to changes in vegetation structure and food supply, or population growth by alien birds. Transmission of avian malaria (Plasmodium relictum) and avian poxvirus is forcast to increase with the upslope movement of mosquitoes in a warming climate (Benning et al. 2002; Atkinson and LaPointe, in press; LaPointe et al., in press). Both diseases are certainly present at Hakalau, although infrequent at the higher elevations considered in our study (VanderWerf 2001, Freed et al. 2005). Evidence for explosive increases in two other threats—Japanese White-eyes and ectoparasites—has been recently reported from the southwestern portion of Hakalau by L. Freed and collaborators (Freed, Cann, et al. 2008;

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Freed, Medeiros, et al. 2008). Their findings have generated much controversy, and further study is needed to validate these claims.

Earlier, we raised a potentially important point about survey methodology at the refuge, that the obvious increase in vegetation structure and density could interfere with counts or at least violate the assumption that count conditions remain constant. While we found statistical evidence for changes in detection probabilities for only one species (Hawai‘i ‘Elepaio), it nevertheless remains the impression of bird counters at Hakalau that the birds are increasingly difficult to see because of the thick undergrowth, however much they can still be heard. For purposes of estimating population densities, it is better to have observers encounter birds at high rates than to rely on analytical corrections for estimating ever-greater proportions of missed birds. Not being able to see the birds may also interfere with confirming identification of confusing calls, particularly for the rare endangered species.

A related issue is that the population of qualified bird counters at the refuge has itself changed. Recent, sharp declines in the pool of active field personnel has resulted in at least a 50% drop in number of counters over the last decade (Hawai‘i Forest Bird Interagency Database, unpubl. data), and those remaining are older (i.e., possibly suffering hearing loss) and/or with less recent field experience with the Hakalau birds. Increased recruitment, training, and evaluation of counters may improve bird counts at the refuge.

Ultimately, continued annual monitoring and updated trends analyses may reveal more conclusive patterns in bird trends as forest regeneration on the refuge advances and the birds have additional time to respond to forest recovery, unless existing or new threats increase and over-ride the benefits of improved habitat. The results of habitat management and bird monitoring at Hakalau Forest National Wildlife Refuge will be watched closely by all involved in the recovery of Hawaiian forest birds. Many similar restoration projects involving tens of thousands of hectares of formerly grazed lands and degraded forest have been started by Hawai‘i Volcanoes National Park, Hawai‘i Division of Forestry and Wildlife, The Nature Conservancy of Hawai‘i, Kamehameha Schools, and others on Hawai‘i Island, and by diverse partners of the Leeward Haleakalā Watershed Partnership on Maui. Bird trends at Hakalau are the first results of efforts to achieve recovery for endangered Hawaiian forest birds based on habitat restoration. Sorting out what these results mean will be an important next step in understanding the direction of forest bird recovery on managed lands.

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ACKNOWLEDGMENTS Analyses of the bird monitoring data from Hakalau were conducted by the

Hawai‘i Forest Bird Interagency Database Project, a project of the U.S. Geological Survey-Pacific Island Ecosystems Research Center (PIERC) and the following cooperating agencies: Pacific Islands Office of the U.S. Fish and Wildlife Service, U.S. Forest Service, U.S. National Park Service, U.S. Geological Survey-Pacific Basin Information Node, University of Hawai‘i Pacific Cooperative Studies Unit, Hawai‘i Division of Forestry and Wildlife, Hawai‘i Gap Analysis Program, Kamehameha Schools, Hawai‘i Natural Heritage Program, and The Nature Conservancy of Hawai‘i. We especially thank the managers and field biologists who collected the data and worked so hard to maintain a core group of trained counters. This manuscript was improved by comments from S. Conant, H. Freifeld, D. Leonard, L. Mehrhoff, and E. VanderWerf. We also thank the numerous interns that assisted with the preparation of data described here. The study was funded by the Pacific Islands Office of the Fish and Wildlife Service and by PIERC. Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Tab

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cha

nge

(% c

hang

e ov

er 2

5 ye

ars)

are

als

o pr

ovid

ed.

Spec

ies

Surv

ey

β̂ (9

5% c

redi

ble

inte

rval

) D

eclin

ing

P ˆ

ϕ<

N

eglig

ible

P

ˆl

βϕ

<<

In

crea

sing

P

ˆu

βϕ

>

Tren

d

Haw

ai‘i

‘Ele

paio

M

id 1

987-

2007

0.

0134

(0.0

070

– 0.

0197

) 0

0.10

8 0.

892

▲ 3

8%

M

id 1

999-

2007

-0

.026

6 (-

0.04

90 –

-0.0

043)

0.

901

0.09

9 <0

.001

48%

Lo

w 1

999-

2007

0.

0005

(-0.

0286

– 0

.029

2)

0.19

9 0.

527

0.27

4 In

c 1%

‘Ōm

a‘o

Mid

198

7-20

07

0.00

98 (0

.005

7 –

0.01

39)

0 0.

411

0.58

9 ~Δ

26%

M

id 1

999-

2007

-0

.003

8 (-

0.01

60 –

0.0

084)

0.

097

0.88

6 0.

017

▬ 9

%

Lo

w 1

999-

2007

-0

.019

0 (-

0.03

65 –

-0.0

015)

0.

784

0.21

5 0.

001

▼ 3

7%

Haw

ai‘i

‘Am

akih

i M

id 1

987-

2007

-0

.005

3 (-

0.00

84 –

-0.0

021)

<0

.001

1.

000

0 ▬

12%

M

id 1

999-

2007

-0

.059

6 (-

0.07

04 –

-0.0

489)

1.

000

0 0

▼ 7

7%

Lo

w 1

999-

2007

-0

.032

3 (-

0.05

25 –

-0.0

013)

0.

978

0.02

2 <0

.001

55%

U

p 19

87-2

007

0.09

43 (0

.068

5 –

0.12

42)

0 0

1.00

0 ▲

769

%

‘Aki

apōlā‘

au

M

id 1

987-

2007

0.

0414

(0.0

191

– 0.

0647

) <0

.001

0.

003

0.99

7 ▲

165

%

M

id 1

999-

2007

-0

.019

7 (-

0.08

92 –

0.0

481)

0.

587

0.21

3 0.

200

Inc

38%

Lo

w 1

999-

2007

-0

.099

7 (-

0.20

81 –

-0.0

061)

0.

966

0.02

3 0.

011

▼ 9

2%

19

Page 26: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

Tab

le 1

. T

rend

s in

fore

st b

ird

dens

ity a

t Hak

alau

For

est N

atio

nal W

ildlif

e R

efug

e co

nt.

Spec

ies

Surv

ey

β̂ (9

5% c

redi

ble

inte

rval

) D

eclin

ing

P ˆ

ϕ<

N

eglig

ible

P

ˆl

βϕ

<<

In

crea

sing

P

ˆu

βϕ

>

Tren

d

Haw

ai‘i

Cre

eper

M

id 1

987-

2007

0.

0167

(0.0

064

– 0.

0271

) 0

0.08

1 0.

919

▲ 4

9%

M

id 1

999-

2007

-0

.010

6 (-

0.04

33 –

0.0

219)

0.

467

0.41

9 0.

114

Inc

23%

Lo

w 1

999-

2007

0.

0219

(-0.

0137

– 0

.057

1)

0.03

1 0.

212

0.75

7 ▲

68%

Haw

ai‘i

‘Āke

pa

Mid

198

7-20

07

0.00

88 (-

0.00

07 –

0.0

185)

<0

.001

0.

542

0.45

8 ~Δ

24%

M

id 1

999-

2007

-0

.049

1 (-

0.08

21 –

-0.0

166)

0.

988

0.01

2 <0

.001

70%

Lo

w 1

999-

2007

0.

0447

(0.0

075

– 0.

0818

) 0.

001

0.03

0 0.

969

▲ 1

86%

‘I‘iw

i M

id 1

987-

2007

-0

.001

1 (-

0.00

37 –

0.0

015)

0

1.00

0 0

▬ 3

%

M

id 1

999-

2007

-0

.045

9 (-

0.05

46 –

-0.0

372)

1.

000

0 0

▼ 6

8%

Lo

w 1

999-

2007

-0

.009

8 (-

0.02

24 –

0.0

027)

0.

371

0.62

8 0.

001

~∇ 2

1%

U

p 19

87-2

007

0.03

32 (-

0.00

72 –

0.0

814)

0.

014

0.12

0 0.

866

▲ 1

19%

‘Apa

pane

M

id 1

987-

2007

-0

.001

9 (-

0.00

52 –

0.0

015)

0

1.00

0 0

▬ 4

%

M

id 1

999-

2007

-0

.063

1 (-

0.07

37 –

-0.0

525)

1.

000

0 0

▼ 7

9%

Lo

w 1

999-

2007

-0

.015

5 (-

0.02

92 –

-0.0

020)

0.

698

0.30

2 <0

.001

~∇

31%

U

p 19

87-2

007

0.03

07 (0

.001

2 –

0.06

34)

0.00

2 0.

079

0.91

9 ▲

107

%

Red

-bill

ed L

eiot

hrix

M

id 1

987-

2007

-0

.008

2 (-

0.01

48 –

-0.0

016)

0.

134

0.86

6 0

▬ 1

8%

M

id 1

999-

2007

-0

.072

5 (-

0.09

14 –

-0.0

539)

1.

000

0 0

▼ 8

4%

Lo

w 1

999-

2007

-0

.038

7 (-

0.06

18 –

-0.0

160)

0.

990

0.01

0 <0

.001

61%

20

Page 27: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

Tab

le 1

. T

rend

s in

fore

st b

ird

dens

ity a

t Hak

alau

Nat

iona

l Wild

life

Ref

uge

cont

.

Spec

ies

Surv

ey

β̂ (9

5% c

redi

ble

inte

rval

) D

eclin

ing

P ˆ

ϕ<

N

eglig

ible

P

ˆl

βϕ

<<

In

crea

sing

P

ˆu

βϕ

>

Tren

d

Japa

nese

Whi

te-e

ye

Mid

198

7-20

07

0.00

68 (0

.000

2 –

0.01

34)

0 0.

773

0.22

7 ▬

18%

M

id 1

999-

2007

0.

0135

(-0.

0047

– 0

.031

6)

0.00

3 0.

326

0.67

1 ~Δ

38%

Lo

w 1

999-

2007

0.

0510

(0.0

199

– 0.

0823

) <0

.001

0.

004

0.99

6 ▲

230

%

U

p 19

87-2

007

0.13

98 (0

.107

8 –

0.17

58)

0 0

1.00

0 ▲

2,2

12%

Nor

ther

n C

ardi

nal

Mid

198

7-20

07

-0.0

090

(-0.

0219

– 0

.003

7)

0.32

8 0.

670

0.00

2 ~∇

20%

M

id 1

999-

2007

-0

.050

9 (-

0.09

59 –

0.0

072)

0.

960

0.03

7 0.

003

▼ 7

1%

Lo

w 1

999-

2007

N

A

N

A

Hou

se F

inch

M

id 1

987-

2007

-0

.052

9 (-

0.07

89 –

-0.0

292)

0.

999

<0.0

01

0 ▼

73%

M

id 1

999-

2007

-0

.118

6 (-

0.18

24 –

-0.0

597)

0.

999

<0.0

01

<0.0

01

▼ 9

5%

Lo

w 1

999-

2007

N

A

N

A

U

p 19

87-2

007

0.03

76 (0

.017

4 –

0.05

92)

0 0.

003

0.99

7 ▲

142

%

21

Page 28: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

Tab

le 2

. Pop

ulat

ion

abun

danc

e es

timat

es fo

r na

tive

and

alie

n bi

rds i

n th

e up

per,

mid

dle

and

low

er st

udy

area

s, an

d to

tal b

ird

abun

danc

es

in th

e su

rvey

ed p

ortio

n of

Hak

alau

For

est N

atio

nal W

ildlif

e R

efug

e in

200

7. A

bund

ance

was

cal

cula

ted

as b

ird d

ensi

ty ti

mes

the

area

of e

ach

stra

ta (

1,31

4 ha

; 3,3

73 h

a; a

nd 1

,998

ha

in th

e up

per,

mid

dle

and

low

er s

trata

, res

pect

ivel

y), a

nd 9

5% C

I lim

its w

ere

pres

ente

d in

par

enth

eses

. D

ensi

ty e

stim

ates

are

ava

ilabl

e in

App

endi

ces 3

, 4, a

nd 5

. Sp

ecie

s U

pper

M

iddl

e Lo

wer

To

tal A

bund

ance

Haw

ai‘i

‘Ele

paio

0

6,91

5 (5

,397

, 8,8

71)

8,43

2 (6

,633

, 10,

689)

15

,347

(12,

030,

19,

560)

‘Ōm

a‘o

0 3,

778

(3,1

71, 4

,452

) 4,

356

(3,7

36, 5

,075

) 8,

134

(6,9

07, 9

,527

)

Haw

ai‘i

‘Am

akih

i 6,

885

(5,2

56, 9

,014

) 12

,109

(10,

321,

14,

167)

8,

212

(6,9

13, 9

,750

) 27

,206

(22,

490,

32,

931)

‘Aki

apōlā‘

au

0 27

0 (1

35, 4

72)

140

(40,

440

) 41

0 (1

75, 9

12)

Haw

ai‘i

Cre

eper

0

2,26

0 (1

,383

, 3,7

44)

3,69

6 (2

,238

, 6,0

74)

5,95

6 (3

,621

, 9,8

18)

Haw

ai‘i

‘Āke

pa

0 3,

103

(2,3

27, 4

,149

) 3,

736

(2,8

57, 4

,895

) 6,

839

(5,1

84, 9

,044

)

‘I‘iw

i 3,

377

(1,6

56, 6

,872

) 26

,208

(22,

329,

30,

762)

31

,668

(28,

452,

35,

225)

61

,253

(52,

437,

72,

859)

‘Apa

pane

3,

482

(2,1

16, 5

,742

) 16

,258

(13,

998,

18,

923)

21

,538

(19,

261,

24,

096)

41

,278

(35,

375,

48,

761)

Red

-bill

ed L

eiot

hrix

0

2,83

3 (2

,361

, 3,4

07)

3,49

7 (2

,917

, 4,1

76)

6,33

0 (5

,278

, 7,5

83)

Japa

nese

Whi

te-e

ye

4,82

2 (3

,443

, 6,7

54)

7,79

2 (6

,679

, 9,0

40)

6,95

3 (5

,794

, 8,3

32)

19,5

67 (1

5,91

6, 2

4,12

6)

Nor

ther

n C

ardi

nal

0 37

1 (2

70, 5

06)

0 37

1 (2

70, 5

06)

Hou

se F

inch

47

3 (2

23, 9

99)

270

(135

, 540

) 0

743

(358

, 1,5

39)

22

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Table 3. Trends in annual forest bird detection probabilities at Hakalau Forest National Wildlife Refuge. Results of Bayesian trends (slope and SE) in the middle stratum (1987-2007) for each species are shown, along with the posterior probabilities and an interpretation of trend (see Table 1 caption for explanations). The trend was based on a 10% change in detection probabilities over 25 years. Strong and very strong evidence of a trend are highlighted in bold. Detection probabilities have not significantly decreased over time despite increasing vegetation cover, except for Hawai‘i ‘Elepaio. In contrast, detection probabilities for Red-billed Leiothrix and Northern Cardinal have increased over time. Species Slope SE Declining Negligible Increasing Trend

Hawai‘i ‘Elepaio -0.0184 0.0072 0.826 0.173 0.001 ▼

‘Ōma‘o -0.0141 0.0088 0.599 0.395 0.006 Inc

Hawai‘i ‘Amakihi -0.0002 0.0082 0.075 0.809 0.116 ▬

‘Akiapōlā‘au1 0.0052 0.0145 Inc

Hawai‘i Creeper2 -0.0076 0.0084 Inc

Hawai‘i ‘Ākepa -0.0046 0.0105 0.234 0.679 0.087 Inc

‘I‘iwi -0.0039 0.0079 0.149 0.805 0.046 ▬

‘Apapane -0.0033 0.0101 0.189 0.711 0.100 ▬

Red-billed Leiothrix 0.0204 0.0137 0.010 0.190 0.800 ▲

Japanese White-eye -0.0001 0.0104 0.121 0.707 0.172 ▬

Northern Cardinal 0.0230 0.0125 0.003 0.125 0.872 ▲

House Finch 0.0034 0.0134 0.117 0.565 0.318 Inc

1 Trend based on least squares regression of log transformed detection probabilities: F1,8 = 0.126, p = 0.73. 2 Trend based on least squares regression of log transformed detection probabilities: F1,19 = 0.820, p = 0.38.

Page 30: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

Figu

re 1

. H

akal

au F

ores

t Nat

iona

l Wild

life

Ref

uge

(hea

vy o

utlin

e) r

elat

ive

to g

ener

al la

ndco

ver

type

s (p

anel

A; f

ores

t - d

ark;

pas

ture

- lig

ht) f

rom

a

Lan

dsat

ET

M im

age.

Sur

vey

stat

ions

(pan

el B

) spa

n th

e up

per,

mid

dle,

and

low

er s

tudy

are

as, e

ach

with

diff

eren

t sur

vey

and

reso

urce

man

agem

ent h

isto

ries.

Tran

sect

s mon

itore

d by

the

refu

ge li

e w

ithin

the

shad

ed a

rea,

whe

reas

tran

sect

s sam

pled

by

the

Haw

aii F

ores

t Bird

Sur

vey

of 1

977

can

be id

entif

ied

beca

use

they

cr

oss b

oth

shad

ed a

nd u

nsha

ded

area

s.

24

Page 31: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

25

Figure 2. Density estimates over time for the eight native bird species at Hakalau Forest NWR. Density estimates (birds/ha and 95% CI) in the middle study area (filled circles) are fitted with trend lines for 1987 to 2007 (heavy line) and 1999 to 2007 (light line), and in the lower study area (open circles) from 1999 to 2007 (dashed line). A reanalysis of the 1977 HFBS densities were presented for illustrative purposes and were not included in the trend analyses. In the middle study area, negligible trends were observed in the full data set from 1987 to 2007 for all native species except Hawai‘i ‘Elepaio, ‘Akiapōlā‘au, and Hawai‘i Creeper populations, which showed strong evidence of increasing trends. However, during the last 9-years most species showed a declining trajectory.

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Figure 3. Density estimates over time for the four most prevalent alien bird species at Hakalau Forest NWR. (see Fig. 2 caption for explanation). Stable trends were observed in the middle study area for all alien species except the House Finch, which showed evidence of decreasing trend.

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27

Figure 4. Density estimates over time for five species in the reforested pasture (upper study area) at Hakalau Forest NWR. (see Fig. 2 caption for explanation). All birds here showed strong or very strong evidence of increasing trends.

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28

0

2

4

6

8

10

12

14

16

18

1975 1985 1995 2005

Year

Den

sity

& 9

5% C

I

.

Figure 5. Density estimates calculated from survey-specific models (open diamonds), post-filtering models (closed circles), and the global model (dashes) for Hawai‘i ‘Amakihi in the middle study area. Post-filtering and survey-specific modeling approaches had good agreement (64%), whereas there was lower agreement with the global model.

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Figure 6. Native passerine population trends in five regions of Hawai‘i Island: (1) Hakalau Forest Unit of Hakalau Forest NWR, (2) Central Windward, (3) Ka‘ū, (4) Kona Forest Unit of Hakalau Forest NWR, and (5) Pu‘u Wa‘awa‘a Wildlife Sanctuary on Mt. Hualālai. Trends are based on current changes in density and species’ range (see Gorresen et al., in press). The symbols ▲, ▼, S, and X indicate increasing trends, decreasing trends, a stable population, and a historically recent extirpation, respectively. A question mark refers to uncertainty in the trend assessment resulting from high variability in estimated densities. Shading depicts overlapping species’ ranges, and darker shading indicates relatively higher species richness. In general, bird populations are doing better in Hakalau, a large actively managed tract of upper elevation forest habitat.

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Appendix 1. Model Selection and AIC.

Akiake’s Information Criterion (AIC) is an efficient quantitative method for

model selection that balances bias and variance (Burnham and Anderson 2002).

However, AIC does not partition the variance into separate components of model and

sampling error but instead assesses the total efficiency of how well the model

approximates the data. We limited the amount of estimator uncertainty attributed to

model error at 70%. Thus, 30% or more to the estimator variance comes from the

sampling error—the actual variability in detecting birds.

This process ensures precise estimates by controlling the amount of model

variance. To avoid unnecessary risk of a biased estimator, we included in our set of

candidate models those with up to two adjustment terms in the series expansion, which

allow a variety of shapes for the detection function, and we ensured that the candidate

detection functions possessed a shoulder near zero distance and for a small distance from

the point. We used AIC to select from this set of candidate models the most

parsimonious one that met these requirements. Ranking by AIC is an objective criterion

that identifies the model that best represents the data. However, AIC is not sufficiently

sensitive to reliably distinguish among the models ranked within four AIC units of the

minimum AIC value. For that purpose we chose the most parsimonious model to

calculate annual density estimates. There is compelling evidence to choose a simpler

model (with fewer parameters) when it has the lowest AIC value because AIC

preferentially weights models with more parameters than models with only a few

parameters (Link and Barker 2006). Thus, the model that estimates a separate detection

probability for each survey is usually included in the top ranked models. In fact, the fully

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31

parameterized model with survey-specific detection probabilities was in the top three

models for all species we investigated.

This selection process may result in a model that is too simple (underfitted),

yielding a highly precise but biased estimator. However, the chosen models generated a

global density similar to that of all the candidate models and had low CV. It is possible

that all of the models are biased to some degree, but the selected models satisfy the model

robustness, pooling robustness, and shape criteria.

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32

Appendix 2. Species Data and Models.

A. Numbers of detections of each species used to calculate population densities, by study area.

Species Middle Study Area Lower Study Area Upper Study AreaHawai‘i ‘Elepaio 3,262 871 27 ‘Ōma‘o 7,853 1,649 26 Hawai‘i ‘Amakihi 15,619 1,651 571 ‘Akiapōlā‘au 335 115 8 Hawai‘i Creeper 1,926 730 4 Hawai‘i ‘Ākepa 2,346 710 1 ‘I‘iwi 23,346 4,333 323 ‘Apapane 17,783 3,866 586 Red-billed Leiothrix 6,275 1,514 44 Japanese White-eye 3,881 698 448 Northern Cardinal 879 13 115 House Finch 896 29 904

B. Detection function parameters used to derive population densities for each species. Species Truncation Key Model Adjustment Terms Covariates Hawai‘i ‘Elepaio 58.0 Half normal None Observer ‘Ōma‘o 83.0 Hazard rate None Observer Hawai‘i ‘Amakihi 58.0 Half normal None Observer ‘Akiapōlā‘au 83.0 Hazard rate None None Hawai‘i Creeper 59.3 Hazard rate Cosine (2) None Hawai‘i ‘Ākepa 59.1 Hazard rate None Observer ‘I‘iwi 58.0 Half normal None None ‘Apapane 60.0 Hazard rate None None Red-billed Leiothrix 72.0 Hazard rate Cosine (2,3) Observer Japanese White-eye 53.2 Hazard rate Simple poly (4,6) Observer Northern Cardinal 115.3 Half normal None Cloud House Finch 98.0 Hazard rate None None

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33

C. Histograms of bird detections used to calculate population estimates. The best fit lines for these data were modeled with program DISTANCE.

0.0

0.5

1.0

1.5

2.0

2.5

0 10 20 30 40 50 60

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 20 40 60 80

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 10 20 30 40 50 60

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 20 40 60 80

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 10 20 30 40 50

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 10 20 30 40 50 60

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0 10 20 30 40 50

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.5

1.0

1.5

2.0

2.5

0 10 20 30 40 50 60

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

Hawai‘i ‘Elepaio ‘Ōma‘o

Hawai‘i ‘Amakihi ‘Akiapōlā‘au

Hawai‘i Creeper Hawai‘i ‘Ākepa

‘I‘iwi ‘Apapane

Page 40: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

34

Appendix 2. C. Histograms of bird detections used to calculate population estimates, cont.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 20 40 60 80

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 10 20 30 40 50

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 20 40 60 80 100 120

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 20 40 60 80 100 120

PERPENDICULAR DISTANCE (m)

DET

ECTI

ON

PR

OBA

BILI

TY

Red-billed Leiothrix Japanese White-eye

Northern Cardinal House Finch

Page 41: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

App

endi

x 3.

Pop

ulat

ion

dens

ity e

stim

ates

for

nat

ive

and

alie

n bi

rds

in t

he m

iddl

e st

udy

area

at

Hak

alau

For

est

NW

R f

rom

19

77 to

200

7 (s

ee F

igs.

2, 3

). Po

pula

tion

dens

ities

of b

irds/

ha a

re g

iven

with

SE

in p

aren

thes

es a

nd 9

5% C

I lim

its in

bra

cket

s.

A.

Nat

ive

bird

s. Y

ear

Haw

ai‘I

‘Ele

paio

‘Ō

ma‘

o H

awai

‘i ‘A

mak

ihi

‘Aki

apōlā‘

au

Haw

ai‘i

Cre

eper

H

awai

‘i ‘Ā

kepa

‘I‘

iwi

‘Apa

pane

1977

3.

64 (0

.345

) [3

.02,

4.3

9]

1.14

(0.0

89)

[0.9

8, 1

.33]

3.

70 (0

.424

) [2

.95,

4.6

4]

0.11

(0.0

46)

[0.0

5, 0

.25]

0.

39 (0

.317

) [0

.09,

1.6

0]

0.45

(0.1

06)

[0.2

8, 0

.71]

13

.92

(1.0

94)

[11.

91, 1

6.26

] 4.

81 (0

.494

) [3

.92,

5.8

9]

1987

2.

75 (0

.321

) [2

.19,

3.4

5]

2.67

(0.1

67)

[2.3

6, 3

.02]

14

.39

(0.8

36)

[12.

84, 1

6.13

] 0.

12 (0

.035

) [0

.06,

0.2

1]

1.31

(0.3

13)

[0.8

2, 2

.08]

1.

46 (0

.251

) [1

.04,

2.0

5]

25.2

2 (1

.306

) [2

2.78

, 27.

92]

14.4

1 (0

.691

) [1

3.11

, 15.

83]

1988

1.

87 (0

.179

) [1

.55,

2.2

5]

1.62

(0.1

34)

[1.3

8, 1

.91]

4.

54 (0

.333

) [3

.93,

5.2

5]

0.10

(0.0

27)

[0.0

6, 0

.17]

0.

33 (0

.222

) [0

.10,

1.1

2]

0.84

(0.1

25)

[0.6

3, 1

.13]

8.

56 (0

.691

) [7

.30,

10.

03]

3.84

(0.4

60)

[3.0

4, 4

.85]

19

89

2.09

(0.2

31)

[1.6

9, 2

.60]

1.

45 (0

.091

) [1

.28,

1.6

4]

10.2

7 (0

.547

) [9

.25,

11.

40]

0.04

(0.0

22)

[0.0

1, 0

.11]

0.

54 (0

.256

) [0

.22,

1.3

3]

0.81

(0.1

54)

[0.5

6, 1

.17]

22

.42

(0.9

68)

[20.

59, 2

4.40

] 10

.10

(0.6

03)

[8.9

8, 1

1.35

] 19

90

1.97

(0.2

24)

[1.5

8, 2

.46]

1.

37 (0

.091

) [1

.21,

1.5

7]

12.4

3 (0

.681

) [1

1.16

, 13.

84]

0.07

(0.0

35)

[0.0

2, 0

.18]

1.

27 (0

.448

) [0

.65,

2.5

0]

0.77

(0.1

62)

[0.5

1, 1

.16]

12

.74

(0.7

02)

[11.

43, 1

4.20

] 6.

57 (0

.442

) [5

.76,

7.5

0]

1991

1.

15 (0

.144

) [0

.90,

1.4

7]

0.73

(0.0

56)

[0.6

2, 0

.85]

8.

58 (0

.385

) [7

.85,

9.3

7]

0.06

(0.0

36)

[0.0

2, 0

.18]

0.

46 (0

.321

) [0

.13,

1.6

1]

0.70

(0.1

52)

[0.4

6, 1

.06]

11

.90

(0.6

08)

[10.

76, 1

3.15

] 6.

97 (0

.411

) [6

.21,

7.8

3]

1992

2.

65 (0

.338

) [2

.06,

3.4

0]

1.60

(0.1

12)

[1.3

9, 1

.83]

14

.91

(0.7

20)

[13.

56, 1

6.40

] 0.

05 (0

.030

) [0

.02,

0.1

5]

1.82

(0.4

31)

[1.1

5, 2

.89]

1.

18 (0

.190

) [0

.86,

1.6

2]

21.3

6 (0

.961

) [1

9.55

, 23.

33]

13.3

7 (0

.548

) [1

2.34

, 14.

49]

1993

2.

15 (0

.256

) [1

.70,

2.7

2]

0.97

(0.0

57)

[0.8

7, 1

.09]

11

.67

(0.5

23)

[10.

68, 1

2.74

] 0.

03 (0

.011

) [0

.01,

0.0

6]

0.29

(0.1

38)

[0.1

2, 0

.72]

0.

80 (0

.109

) [0

.61,

1.0

4]

15.6

6 (0

.723

) [1

4.30

, 17.

14]

7.62

(0.5

69)

[6.5

9, 8

.82]

19

94

2.06

(0.2

18)

[1.6

7, 2

.53]

1.

62 (0

.083

) [1

.46,

1.7

9]

7.10

(0.3

34)

[6.4

8, 7

.79]

0.

05 (0

.01 9

) [0

.03,

0.1

0]

1.59

(0.2

99)

[1.1

0, 2

.29]

0.

74 (0

.125

) [0

.53,

1.0

3]

15.5

1 (0

.574

) [1

4.43

, 16.

68]

4.78

(0.3

06)

[4.2

2, 5

.42]

19

95

2.71

(0.2

51)

[2.2

6, 3

.25]

1.

32 (0

.078

) [1

.18,

1.4

9]

8.25

(0.4

18)

[7.4

6, 9

.11]

0.

03 (0

.013

) [0

.01,

0.0

7]

0.83

(0.2

35)

[0.4

8, 1

.44]

0.

73 (0

.131

) [0

.52,

1.0

4]

19.0

1 (0

.662

) [1

7.76

, 20.

36]

5.90

(0.3

11)

[5.3

2, 6

.54]

19

96

2.25

(0.2

16)

[1.8

6, 2

.71]

1.

23 (0

.066

) [1

.11,

1.3

7]

15.2

4 (0

.712

) [1

3.9,

16.

70]

0.10

(0.0

24)

[0.0

7, 0

.16]

2.

34 (0

.519

) [1

.52,

3.6

0]

2.30

(0.3

33)

[1.7

3, 3

.05]

16

.17

(0.5

97)

[15.

04, 1

7.38

] 5.

99 (0

.325

) [5

.39,

6.6

7]

1997

2.

70 (0

.292

) [2

.19,

3.3

4]

2.58

(0.1

50)

[2.3

0, 2

.89]

14

.67

(0.7

04)

[13.

35, 1

6.12

] 0.

09 (0

.034

) [0

.04,

0.1

8]

1.86

(0.3

65)

[1.2

7, 2

.72]

1.

68 (0

.230

) [1

.29,

2.2

0]

29.9

2 (0

.909

) [2

8.18

, 31.

76]

11.0

7 (0

.614

) [9

.93,

12.

35]

1998

1.

97 (0

.226

) [1

.58,

2.4

7]

1.46

(0.0

72)

[1.3

3, 1

.61]

11

.77

(0.5

73)

[10.

70, 1

2.96

] 0.

09 (0

.026

) [0

.05,

0.1

5]

1.53

(0.3

03)

[1.0

4, 2

.25]

1.

33 (0

.203

) [0

.99,

1.7

9]

23.6

2 (0

.718

) [2

2.25

, 25.

07]

10.0

7 (0

.499

) [9

.14,

11.

10]

1999

2.

46 (0

.238

) [2

.03,

2.9

8]

1.73

(0.0

91)

[1.5

6, 1

.92]

8.

78 (0

.557

) [7

.75,

9.9

5]

0.07

(0.0

25)

[0.0

3, 0

.14]

0.

67 (0

.204

) [0

.38,

1.2

1]

0.90

(0.1

36)

[0.6

7, 1

.21]

19

.59

(0.6

41)

[18.

37, 2

0.89

] 10

.01

(0.5

18)

[9.0

4, 1

1.08

] 20

00

3.22

(0.3

43)

[2.6

1, 3

.96]

1.

96 (0

.109

) [1

.76,

2.1

9]

12.7

2 (0

.665

) [1

1.48

, 14.

10]

0.12

(0.0

37)

[0.0

6, 0

.22]

1.

40 (0

.378

) [0

.84,

2.3

6]

1.72

(0.2

49)

[1.3

0, 2

.29]

23

.80

(0.8

90)

[22.

11, 2

5.61

] 11

.63

(0.5

44)

[10.

60, 1

2.75

] 20

01

3.05

(0.3

30)

[2.4

7, 3

.77]

2.

05 (0

.107

) [1

.85,

2.2

7]

12.9

8 (0

.562

) [1

1.92

, 14.

13]

0.20

(0.0

75)

[0.0

9, 0

.41]

1.

04 (0

.141

) [0

.80,

1.3

6]

1.54

(0.2

10)

[1.1

8, 2

.01]

17

.02

(0.7

22)

[15.

66, 1

8.49

] 9.

72 (0

.485

) [8

.81,

10.

72]

35

Page 42: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

App

endi

x 3.

A.

Nat

ive

bird

s con

t. Y

ear

Haw

ai‘I

‘Ele

paio

‘Ō

ma‘

o H

awai

‘i ‘A

mak

ihi

‘Aki

apōlā‘

au

Haw

ai‘i

Cre

eper

H

awai

‘i ‘Ā

kepa

‘I‘

iwi

‘Apa

pane

2002

2.

69 (0

.313

) [2

.15,

3.3

8]

1.92

(0.1

14)

[1.7

1, 2

.16]

11

.63

(0.5

03)

[10.

69, 1

2.66

] 0.

12 (0

.047

) [0

.05,

0.2

5]

2.37

(0.4

26)

[1.6

7, 3

.37]

1.

19 (0

.147

) [0

.93,

1.5

1]

16.1

1 (0

.688

) [1

4.82

, 17.

52]

9.82

(0.5

19)

[8.8

5, 1

0.90

] 20

03

2.94

(0.3

02)

[2.4

0, 3

.59]

1.

70 (0

.110

) [1

.50,

1.9

3]

12.6

0 (0

.731

) [1

1.25

, 14.

12]

0.25

(0.1

18)

[0.1

0, 0

.61]

1.

43 (0

.307

) [0

.94,

2.1

7]

1.44

(0.2

66)

[1.0

0, 2

.06]

16

.90

(0.7

79)

[15.

43, 1

8.50

] 12

.23

(0.6

24)

[11.

06, 1

3.51

] 20

04

2.62

(0.2

71)

[2.1

3, 3

.21]

2.

28 (0

.105

) [2

.09,

2.5

0]

11.6

9 (0

.623

) [1

0.52

, 12.

97]

0.12

(0.0

59)

[0.0

5, 0

.30]

1.

11 (0

.307

) [0

.65,

1.8

9]

1.56

(0.2

15)

[1.1

9, 2

.04]

17

.58

(0.6

98)

[16.

27, 1

9.01

] 7.

48 (0

.379

) [6

.77,

8.2

7]

2005

2.

70 (0

.364

) [2

.07,

3.5

1]

1.49

(0.1

03)

[1.3

0, 1

.71]

9.

90 (0

.595

) [8

.80,

11.

15]

0.12

(0.0

43)

[0.0

6, 0

.24]

1.

51 (0

.341

) [0

.97,

2.3

4]

0.89

(0.1

95)

[0.5

8, 1

.36]

19

.81

(0.9

97)

[17.

95, 2

1.87

] 10

.06

(0.7

30)

[8.7

2, 1

1.60

] 20

06

2.94

(0.3

63)

[2.3

1, 3

.75]

2.

38 (0

.139

) [2

.12,

2.6

7]

10.9

0 (0

.615

) [9

.76,

12.

18]

0.08

(0.0

31)

[0.0

4, 0

.17]

0.

83 (0

.296

) [0

.42,

1.6

4]

0.62

(0.1

16)

[0.4

3, 0

.89]

15

.92

(0.7

66)

[14.

49, 1

7.5]

7.

89 (0

.432

) [7

.08,

8.7

9]

2007

2.

05 (0

.260

) [1

.60,

2.6

3]

1.12

(0.0

95)

[0.9

4, 1

.32]

3.

59 (0

.289

) [3

.06,

4.2

0]

0.08

(0.0

24)

[0.0

4, 0

.14]

0.

67 (0

.173

) [0

.41,

1.1

1]

0.92

(0.1

36)

[0.6

9, 1

.23]

7.

77 (0

.634

) [6

.62,

9.1

2]

4.82

(0.3

70)

[4.1

5, 5

.61]

B

. A

lien

bird

s. Y

ear

Red

-bille

d Le

ioth

rix

Japa

nese

Whi

te-e

ye

Nor

ther

n C

ardi

nal

Hou

se F

inch

19

77

3.18

(0.3

60) [

2.54

, 3.9

8]

3.70

(0.5

07) [

2.82

, 4.8

5]

0.03

(0.0

15) [

0.01

, 0.0

8]

0.29

(0.0

93) [

0.16

, 0.5

4]

1987

3.

00 (0

.273

) [2.

51, 3

.59]

6.

93 (0

.679

) [5.

72, 8

.40]

0.

22 (0

.049

) [0.

14, 0

.34]

0.

63 (0

.234

) [0.

31, 1

.28]

19

88

2.05

(0.2

34) [

1.64

, 2.5

6]

1.97

(0.2

29) [

1.57

, 2.4

7]

0.11

(0.0

33) [

0.07

, 0.2

0]

0.40

(0.1

23) [

0.22

, 0.7

2]

1989

4.

82 (0

.548

) [3.

85, 6

.02]

2.

56 (0

.252

) [2.

11, 3

.11]

0.

19 (0

.043

) [0.

13, 0

.30]

0.

33 (0

.098

) [0.

18, 0

.58]

19

90

3.47

(0.4

21) [

2.74

, 4.4

0]

2.85

(0.3

43) [

2.25

, 3.6

1]

0.17

(0.0

40) [

0.11

, 0.2

7]

0.25

(0.0

91) [

0.12

, 0.5

0]

1991

1.

14 (0

.163

) [0.

86, 1

.51]

1.

40 (0

.445

) [0.

76, 2

.58]

0.

18 (0

.041

) [0.

12, 0

.28]

0.

09 (0

.074

) [0.

02, 0

.38]

19

92

1.17

(0.1

22) [

0.95

, 1.4

3]

3.34

(0.3

53) [

2.72

, 4.1

1]

0.25

(0.0

50) [

0.17

, 0.3

7]

0.54

(0.1

14) [

0.36

, 0.8

2]

1993

1.

38 (0

.155

) [1.

11, 1

.72]

2.

57 (0

.857

) [1.

35, 4

.87]

0.

16 (0

.028

) [0.

11, 0

.22]

0.

13 (0

.043

) [0.

07, 0

.25]

19

94

2.52

(0.2

57) [

2.06

, 3.0

8]

1.29

(0.1

64) [

1.00

, 1.6

5]

0.12

(0.0

22) [

0.08

, 0.1

7]

0.07

(0.0

29) [

0.03

, 0.1

5]

1995

3.

35 (0

.330

) [2.

76, 4

.07]

1.

99 (0

.222

) [1.

60, 2

.47]

0.

15 (0

.030

) [0.

11, 0

.23]

0.

06 (0

.019

) [0.

03, 0

.11]

19

96

3.36

(0.3

26) [

2.78

, 4.0

6]

5.12

(0.4

52) [

4.30

, 6.0

9]

0.29

(0.0

41) [

0.22

, 0.3

8]

0.16

(0.0

54) [

0.08

, 0.3

0]

1997

2.

74 (0

.242

) [2.

31, 3

.26]

2.

87 (0

.305

) [2.

33, 3

.54]

0.

20 (0

.036

) [0.

14, 0

.28]

0.

03 (0

.015

) [0.

01, 0

.08]

20

03

2.53

(0.1

96) [

2.18

, 2.9

5]

2.75

(0.2

19) [

2.35

, 3.2

2]

0.16

(0.0

31) [

0.11

, 0.2

3]

0.40

(0.0

76) [

0.27

, 0.5

8]

2004

2.

51 (0

.170

) [2.

20, 2

.87]

3.

68 (0

.349

) [3.

05, 4

.43]

0.

23 (0

.039

) [0.

16, 0

.32]

0.

11 (0

.041

) [0.

06, 0

.23]

20

05

1.82

(0.1

66) [

1.52

, 2.1

8]

4.42

(0.4

02) [

3.70

, 5.2

9]

0.14

(0.0

28) [

0.10

, 0.2

1]

0.26

(0.0

60) [

0.17

, 0.4

1]

2006

2.

85 (0

.190

) [2.

50, 3

.25]

3.

65 (0

.296

) [3.

12, 4

.28]

0.

08 (0

.020

) [0.

05, 0

.13]

0.

16 (0

.086

) [0.

06, 0

.43]

20

07

0.84

(0.0

79) [

0.70

, 1.0

1]

2.31

(0.1

78) [

1.98

, 2.6

8]

0.11

(0.0

17) [

0.08

, 0.1

5]

0.08

(0.0

28) [

0.04

, 0.1

6]

36

Page 43: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

App

endi

x 4.

Po

pula

tion

dens

ity e

stim

ates

for

nat

ive

and

alie

n bi

rds

in t

he lo

wer

stu

dy a

rea

at H

akal

au F

ores

t N

WR

fro

m

1999

to 2

007

(see

Fig

s. 2,

3).

Popu

latio

n de

nsiti

es o

f bird

s/ha

are

giv

en w

ith S

E in

par

enth

eses

and

95%

CI l

imits

in b

rack

ets.

A.

Nat

ive

bird

s. Y

ear

Haw

ai‘I

‘Ele

paio

‘Ō

ma‘

o H

awai

‘i ‘A

mak

ihi

‘Aki

apōlā‘

au

Haw

ai‘i

Cre

eper

H

awai

‘i ‘Ā

kepa

‘I‘

iwi

‘Apa

pane

1999

3.

49 (0

.376

) [2

.82,

4.3

1]

2.35

(0.1

33)

[2.1

1, 2

.63]

5.

92 (0

.376

) [5

.22,

6.7

1]

0.30

(0.0

86)

[0.1

7, 0

.52]

1.

34 (0

.402

) [0

.75,

2.3

9]

1.73

(0.2

10)

[1.3

6, 2

.19]

18

.45

(0.6

37)

[17.

24, 1

9.75

] 11

.22

(0.5

17)

[10.

25, 1

2.29

] 20

00

3.71

(0.4

45)

[2.9

4, 4

.70]

1.

95 (0

.130

) [1

.71,

2.2

3]

6.44

(0.5

49)

[5.4

4, 7

.62]

0.

10 (0

.042

) [0

.05,

0.2

2]

2.36

(0.6

30)

[1.4

1, 3

.96]

1.

29 (0

.206

) [0

.94,

1.7

6]

20.8

2 (0

.993

) [1

8.95

, 22.

87]

9.50

(0.5

68)

[8.4

5, 1

0.69

] 20

01

2.97

(0.3

66)

[2.3

3, 3

.79]

1.

82 (0

.124

) [1

.59,

2.0

8]

6.34

(0.5

19)

[5.3

9, 7

.45]

0.

24 (0

.109

) [0

.10,

0.5

7]

1.38

(0.2

08)

[1.0

2, 1

.85]

1.

48 (0

.238

) [1

.08,

2.0

3]

14.2

5 (0

.727

) [1

2.89

, 15.

76]

10.7

0 (0

.598

) [9

.59,

11.

95]

2002

4.

43 (0

.472

) [3

.60,

5.4

7]

1.90

(0.1

25)

[1.6

7, 2

.16]

6.

70 (0

.420

) [5

.92,

7.5

8]

0.30

(0.1

11)

[0.1

5, 0

.61]

3.

25 (0

.580

) [2

.30,

4.6

1]

1.63

(0.2

00)

[1.2

8, 2

.07]

12

.59

(0.6

62)

[11.

35, 1

3.96

] 10

.40

(0.5

64)

[9.3

5, 1

1.57

] 20

03

3.15

(0.3

72)

[2.5

0, 3

.98]

1.

64 (0

.146

) [1

.37,

1.9

5]

5.35

(0.5

45)

[4.3

8, 6

.55]

0.

08 (0

.049

) [0

.02,

0.2

4]

3.07

(0.6

45)

[2.0

4, 4

.62]

2.

01 (0

.369

) [1

.40,

2.8

8]

17.9

5 (1

.134

) [1

5.84

, 20.

33]

10.6

2 (0

.641

) [9

.43,

11.

96]

2004

2.

14 (0

.311

) [1

.61,

2.8

4]

1.71

(0.1

19)

[1.4

9, 1

.96]

5.

63 (0

.479

) [4

.76,

6.6

6]

0.24

(0.1

20)

[0.1

0, 0

.61]

1.

20 (0

.337

) [0

.70,

2.0

6]

2.10

(0.2

85)

[1.6

0, 2

.74]

18

.50

(1.1

23)

[16.

41, 2

0.86

] 6.

33 (0

.413

) [5

.57,

7.2

0]

2005

4.

14 (0

.595

) [3

.12,

5.5

0]

1.74

(0.1

47)

[1.4

8, 2

.06]

6.

40 (0

.588

) [5

.33,

7.6

9]

0.10

(0.0

49)

[0.0

4, 0

.25]

4.

47 (0

.970

) [2

.93,

6.8

2]

2.93

(0.6

42)

[1.9

1, 4

.51]

20

.07

(1.0

68)

[18.

07, 2

2.30

] 13

.25

(0.9

68)

[11.

47, 1

5.29

] 20

06

3.09

(0.4

30)

[2.3

5, 4

.07]

1.

81 (0

.138

) [1

.55,

2.1

0]

5.16

(0.4

68)

[4.3

1, 6

.17]

0.

15 (0

.068

) [0

.06,

0.3

5]

1.21

(0.4

5 6)

[0.5

9, 2

.48]

1.

57 (0

.314

) [1

.06,

2.3

3]

16.2

4 (1

.034

) [1

4.31

, 18.

42]

7.42

(0.4

20)

[6.6

3, 8

.30]

20

07

4.22

(0.5

11)

[3.3

2, 5

.35]

2.

18 (0

.169

) [1

.87,

2.5

4]

4.11

(0.3

57)

[3.4

6, 4

.88]

0.

07 (0

.044

) [0

.02,

0.2

2]

1.85

(0.4

74)

[1.1

2, 3

.04]

1.

87 (0

.256

) [1

.43,

2.4

5]

15.8

5 (0

.859

) [1

4.24

, 17.

63]

10.7

8 (0

.612

) [9

.64,

12.

06]

B.

Alie

n bi

rds.

Yea

r R

ed-b

illed

Leio

thrix

Ja

pane

se W

hite

-eye

N

orth

ern

Car

dina

l H

ouse

Fin

ch

1999

2.

75 (0

.233

) [2.

33, 3

.25]

2.

28 (0

.281

) [1.

79, 2

.90]

0.

02 (0

.013

) [0.

01, 0

.07]

0.

21 (0

.070

) [0.

11, 0

.40]

20

00

3.91

(0.3

81) [

3.23

, 4.7

4]

2.29

(0.3

12) [

1.75

, 2.9

9]

0.02

(0.0

11) [

0.01

, 0.0

6]

0.08

(0.0

36) [

0.03

, 0.1

9]

2001

2.

77 (0

.240

) [2.

33, 3

.28]

2.

31 (0

.322

) [1.

75, 3

.04]

0.

02 (0

.013

) [0.

01, 0

.07]

0.

01 (0

.010

) [0.

01, 0

.05]

20

02

3.63

(0.3

13) [

3.06

, 4.3

0]

2.43

(0.2

88) [

1.92

, 3.0

7]

0.01

(0.0

09) [

0.01

, 0.0

5]

0.01

(0.0

10) [

0.01

, 0.0

5]

2003

2.

67 (0

.244

) [2.

23, 3

.20]

2.

76 (0

.358

) [2.

14, 3

.57]

0.

02 (0

.012

) [0.

01, 0

.06]

0

2004

2.

30 (0

.206

) [1.

92, 2

.74]

3.

12 (0

.420

) [2.

40, 4

.07]

0

0.03

(0.0

32) [

0.01

, 0.1

7]

2005

3.

04 (0

.305

) [2.

49, 3

.71]

2.

67 (0

.438

) [1.

93, 3

.69]

0

0.05

(0.0

50) [

0.01

, 0.2

6]

2006

3.

33 (0

.292

) [2.

80, 3

.96]

2.

83 (0

.399

) [2.

14, 3

.74]

0.

03 (0

.019

) [0.

01, 0

.10]

0

2007

1.

75 (0

.158

) [1.

46, 2

.09]

3.

48 (0

.319

) [2.

90, 4

.17]

0

0

37

Page 44: PASSERINE BIRD TRENDS AT HAKALAU FOREST NATIONAL WILDLIFE REFUGE

App

endi

x 5.

Pop

ulat

ion

dens

ity e

stim

ates

for

nat

ive

and

alie

n bi

rds

in t

he r

efor

este

d pa

stur

e, u

pper

stu

dy a

rea,

at

Hak

alau

Fo

rest

NW

R f

rom

198

7 to

200

7 (s

ee F

ig. 4

). D

ata

wer

e no

t ana

lyze

d fo

r 19

92-1

995

and

1997

bec

ause

less

than

30

stat

ions

wer

e sa

mpl

ed. P

opul

atio

n de

nsiti

es o

f bird

s/ha

are

giv

en w

ith S

E in

par

enth

eses

and

95%

CI l

imits

in b

rack

ets.

Yea

r H

awai

‘i ‘A

mak

ihi

‘I‘iw

i ‘A

papa

ne

Japa

nese

Whi

te-e

ye

Hou

se F

inch

19

87

3.82

(1.2

97) [

1.96

, 7.4

7]

2.47

(1.2

54) [

0.93

, 6.5

4]

5.70

(2.4

36) [

2.48

, 13.

09]

1.36

(0.5

55) [

0.61

, 3.0

1]

1.81

(0.8

08) [

0.77

, 4.2

1]

1988

0.

54 (0

.258

) [0.

21, 1

.36]

0.

25 (0

.253

) [0.

05, 1

.38]

0.

35 (0

.231

) [0.

10, 1

.19]

0.

39 (0

.230

) [0.

13, 1

.18]

0.

85 (0

.380

) [0.

36, 2

.00]

19

89

0.81

(0.3

52) [

0.35

, 1.8

9]

2.17

(1.3

29) [

0.69

, 6.8

4]

1.93

(0.6

41) [

1.00

, 3.7

3]

0.48

(0.1

82) [

0.23

, 1.0

1]

0.72

(0.2

95) [

0.33

, 1.5

8]

1990

0.

91 (0

.406

) [0.

39, 2

.14]

0.

54 (0

.236

) [0.

24, 1

.25]

0.

55 (0

.231

) [0.

24, 1

.23]

0.

37 (0

.195

) [0.

13, 0

.99]

0.

23 (0

.089

) [0.

11, 0

.48]

19

91

0.78

(0.4

57) [

0.26

, 2.3

5]

0.83

(0.4

94) [

0.27

, 2.5

4]

0.73

(0.3

51) [

0.29

, 1.8

4]

0.22

(0.1

45) [

0.06

, 0.7

3]

0.47

(0.3

74) [

0.12

, 1.9

2]

1996

2.

25 (0

.666

) [1.

25, 4

.06]

1.

63 (0

.815

) [0.

63, 4

.26]

0.

79 (0

.410

) [0.

29, 2

.13]

0.

25 (0

.175

) [0.

07, 0

.90]

0.

18 (0

.094

) [0.

06, 0

.48]

19

98

1.94

(0.5

56) [

1.10

, 3.4

4]

1.25

(0.6

50) [

0.46

, 3.3

8]

1.54

(0.6

06) [

0.71

, 3.3

3]

0.68

(0.4

15) [

0.22

, 2.1

3]

0.63

(0.3

37) [

0.23

, 1.7

1]

1999

2.

54 (0

.551

) [1.

65, 3

.93]

1.

32 (0

.610

) [0.

54, 3

.23]

2.

44 (0

.905

) [1.

18, 5

.06]

2.

45 (0

.623

) [1.

48, 4

.07]

2.

42 (0

.529

) [1.

58, 3

.72]

20

00

3.11

(0.8

18) [

1.84

, 5.2

6]

3.02

(1.1

49) [

1.43

, 6.3

8]

3.32

(1.1

29) [

1.69

, 6.5

0]

2.96

(0.7

81) [

1.75

, 5.0

1]

3.14

(0.6

86) [

2.05

, 4.8

2]

2001

3.

24 (0

.827

) [1.

95, 5

.40]

1.

33 (0

.575

) [0.

57, 3

.08]

3.

78 (0

.982

) [2.

25, 6

.35]

2.

15 (0

.636

) [1.

20, 3

.87]

1.

74 (0

.339

) [1.

19, 2

.56]

20

02

3.08

(0.7

00) [

1.95

, 4.8

6]

1.30

(0.6

85) [

0.48

, 3.5

6]

2.25

(0.5

90) [

1.33

, 3.8

0]

3.79

(0.6

26) [

2.72

, 5.2

8]

1.03

(0.2

37) [

0.65

, 1.6

2]

2003

3.

09 (0

.663

) [2.

01, 4

.75]

1.

85 (0

.706

) [0.

88, 3

.92]

2.

61 (0

.692

) [1.

54, 4

.43]

2.

31 (0

.471

) [1.

53, 3

.48]

1.

77 (0

.341

) [1.

21, 2

.59]

20

04

3.49

(0.5

95) [

2.48

, 4.9

2]

2.50

(0.9

01) [

1.23

, 5.0

9]

2.33

(0.5

44) [

1.46

, 3.7

2]

4.84

(0.9

26) [

3.30

, 7.1

0]

1.10

(0.3

46) [

0.60

, 2.0

3]

2005

5.

04 (0

.708

) [3.

80, 6

.70]

2.

16 (0

.884

) [0.

97, 4

.81]

4.

46 (0

.977

) [2.

88, 6

.91]

8.

93 (1

.723

) [6.

06, 1

3.14

] 2.

16 (0

.373

) [1.

54, 3

.04]

20

06

6.25

(0.9

97) [

4.53

, 8.6

3]

1.23

(0.5

23) [

0.53

, 2.8

3]

1.40

(0.4

22) [

0.77

, 2.5

6]

5.55

(1.0

17) [

3.84

, 8.0

4]

1.91

(0.9

73) [

0.73

, 4.9

9]

2007

5.

24 (0

.695

) [4.

00, 6

.86]

2.

57 (0

.921

) [1.

26, 5

.23]

2.

65 (0

.659

) [1.

61, 4

.37]

3.

67 (0

.613

) [2.

62, 5

.14]

0.

36 (0

.138

) [0.

17, 0

.76]

38